If you think Big Data is something only B2C marketers need worry about, you’d be wrong.

As business buyers turn to the digital world to help them explore and solve pressing business problems, marketers will find that the data needed to propel their firms into the digital future is increasingly big.

The challenges we face in closing the gap between the amount of data available and our ability to get value from it are equally big. Nevertheless, to become customer obsessed requires understanding your buyers much better and data is the key to that understanding. During Forrester’s Forum for Marketing Leaders last week, I told B2B marketers that it’s time to make a date with their big data destiny. (The prior link is to our forum coming up in London -- you can also listen to my April 30 webinar to learn more on this topic.)

My colleague Brian Hopkins believes that - to exploit the business opportunity hiding in big piles of data - marketers must understand that data is increasingly:

Do you think you are ready to tackle Big Data because you are pushing the limits of your data Volume, Velocity, Variety and Variability? Take a deep breath (and maybe a cold shower) before you plunge full speed ahead into unchartered territories and murky waters of Big Data. Now that you are calm, cool and collected, ask yourself the following key questions:

What’s the business use case? What are some of the business pain points, challenges and opportunities you are trying to address with Big Data? Are your business users coming to you with such requests or are you in the doomed-for-failure realm of technology looking for a solution?

Are you sure it’s not just BI 101? Once you identify specific business requirements, ask whether Big Data is really the answer you are looking for. In the majority of my Big Data client inquiries, after a few probing questions I typically find out that it's really BI 101: data governance, data integration, data modeling and architecture, org structures, responsibilities, budgets, priorities, etc. Not Big Data.

Why can’t your current environment handle it? Next comes another sanity check. If you are still thinking you are dealing with Big Data challenges, are you sure you need to do something different, technology-wise? Are you really sure your existing ETL/DW/BI/Advanced Analytics environment can't address the pain points in question? Would just adding another node, another server, more memory (if these are all within your acceptable budget ranges) do the trick?